I'm working on my own strong AI project and was pleasantly surprised to find your project because I need computer vision for automatic knowledge acquisition algorithms and I'm writing it in C#. Do you have any interest in developing strong AI? I'll remove my URL if you don't want it posted, but the link to my project is http://www.PracticalAI.org. I think I've figured out how to go about creating it... With automatic knowledge acquisition and effective reasoning algorithms that can use the knowledge well. I'm always looking for others that might be interested.

Well, of course this is interesting and something I would love to have progress in. Having developed Strong AI would change the world tremendously …

I have some comments regarding the thoughts published on your web site …

davidhere40 wrote:With enough effort, artificial intelligence is achievable in a relatively short period of time.

Well, even from this short history review, we may see the amount of effort, which was put into developing strong AI. However, it is not yet done. Your statement sounds really ambitious …

davidhere40 wrote:How to achieve artificial intelligence, as well as why all previous attempts have failed …

The suspicious word here is “all”. You did not say “many” or “most”. Could you be more specific and reference all the fallen projects you’ve reviewed? The fact that we still don’t have developed strong AI, does not mean all existing projects don’t have progress and are moving into wrong direction.

davidhere40 wrote:This project aims to create a system that automatically acquires knowledge of different forms and types …

Since you’ve stated definition of intelligence, it would be also useful to define what knowledge is. Not data, not information, but knowledge …

Well, I think that at this point the idea of the project is not yet something revolutionary new. Yes, gathering knowledge is a feature, but I doubt nobody else was thinking about this.

Of course it is a good thing, that project like this has started and people accumulate and share ideas about creating strong AI. But, as you also have mentioned, there will be a lot more to think about and implement, like how to collect knowledge, how to extract them, store, apply, etc., etc.

Sorry I didn't reply sooner. I forgot you might reply directly on the forum. Well, actually I think I can prove why all AI projects have failed. The reason I say all, is because I have never found a project that I can estimate will lead to strong AI. I probably should say many. But I really would love someone to prove me wrong!

I'm writing an article about everything actually and will be advertising it tremendously when it is done. I think it will be revolutionary for AI research. But to summarize, I believe the reason that AI research has failed is because: whenever given a chance to do AI right or take a short cut, researchers have chosen the short cut. The right way is to base prediction on the fundamental features and factors that determine and cause the behavior we are trying to predict. This is the reason AI research has failed. Whenever given the chance, we have chosen not to automatically acquire the fundamental features, factors and other knowledge required to be intelligent. Why? Because its not easy and the shortcut seems easier. In fact, it requires a way to automatically acquire features and factors of the real world. This requires a direct way to observe the real world (as opposed to observing symbols, such as words, or being given knowledge by the designer). Knowledge cannot be given to the AI manually because knowledge is not something that consists of absolute facts. Knowledge is something that must be acquired, maintained and updated over time. It requires inductive reasoning such as educated guesses, and hypothesis. It is no wonder AI research has failed. The way to acquire those features and factors is through direct access to the features and factors. As far as I know, the best way to do that is through computer vision. But computer vision is very hard and complex. I think we are at the point where we can create strong AI through computer vision with today's technology. We have made great progress over the years, but by the time we did, people were already entrenched in their research efforts in factor-free AI. Also, only recently have computers been fast enough for the algorithms I will be writing to process images.

It is a long argument. But I hope to have a strong article on it in the next week or two (maybe around 3/20/09). I hope you'll read and critique it.

I just put the article/tutorial up on the website. It is just the first page because the article has become too long and overwhelming to write all at once. I'll be spending quite a bit of time updating and perfecting it, adding pages, and updating the website.

<em>andrew.kirillov</em> wrote:As far as I know, the best way to do that is through computer vision.

Well, of course vision plays an important part in knowledge acquisition. But we also need to keep in mind that blind people also may learn and acquire knowledge. People can not only see, but can hear, sense, etc. – all these play important role in knowledge acquisition. Did not you think about generalization? Otherwise, if we make specific system based on vision only, we may get yet another failure …

The reason I chose computer vision, is because when I compared the other methods, I found computer vision to be far superior in acquiring the same knowledge. I made a table with the 5 senses as columns, and different types of features or factors as rows. Then I put yes or no for whether the features could be acquired through the different senses.

As you also mentioned, it is clear that not all the senses are required. People that are blind, deaf, quadriplegic, blind and deaf, etc still manage to become intelligent. Helen Keller and Christopher Nolan are a couple examples. So, I concluded that all that is required is a way to observe the world that allows us to acquire enough knowledge and features. It is also more practical, not to overwhelm the project with the need to implement voice, hearing, vision, motor skills, touch and other sensory inputs. It makes more sense to pick one that is sufficient, yet powerful, like computer vision. That was my reasoning. Hence the name PracticalAI.org The computer might not know that two things taste similar, but I think that such knowledge is fairly unimportant. So, the handicap would be minimal.

With regard to generalization, the only generalization I have found is that most knowledge seems to be useful if it can be a "factor". Factors are the things that cause a result. So, when acquiring knowledge, we are really acquiring factors to help us understand and predict the world around us. And I can't prove it yet, but it seems to me that predicting the world around us is the basis of intelligence.

<em>andrew.kirillov</em> wrote:The computer might not know that two things taste similar, but I think that such knowledge is fairly unimportant.

Well, may be I am getting lost in what you are trying to develop. As you know the idea of Strong AI is to develop Artificial Intelligence which is one same level as human's intelligence or even above. So, I am not really sure you may say that some type of knowledge is not important for AI. Yes, computer (if your strong AI will live in just computer’s body) may not have a chance to taste something, but its strong AI should be able to discuss topics about tastes, wonder about tastes, try to imagine, whish to taste that finally someday, etc. Isn’t it?

Yeah, what I want to develop wouldn't be prevented from thinking about tastes. My goal is not really to make a synthetic human or make it do anything that a human can do. What I, personally, really want is a powerful tool for research. My end goal is not AI at all. It is the technology and knowledge that AI facilitates. My true goal is to eventually cure diseases. Imagine an AI that you could use natural language to command and would be similar to an office worker/employee. Imagine that if one AI learns a lot of knowledge, the others can just search the existing knowledge for anything useful and incorporate it.... Shared knowledge. If all it needed was a powerful desktop computer and a couple cameras, you could put 1000 on a task like curing cancer for maybe just $100K.